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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Amine Oxidation Catalyzed by NO 2

Amine oxidation is a major risk in the deployment of amine scrubbing for CO2 capture from post-combustion flue gas. Oxidation probably occurs by dissolved oxygen at elevated temperature, Fe(III)/Fe(II) shuttling between the absorber and the stripper, and by NO2 in the absorber. Amine selection, dissolved oxygen removal, and solvent reclaiming mitigate oxidation due to dissolved oxygen and iron shuttle mechanism, but not by NO2. This work examines piperazine (PZ) oxidation by NO2 in a bench-scale high gas flow reactor (HGF). PZ is an effective second-generation solvent with high CO2 capacity, fast capture rate, good thermal stability, and good resistance to oxidation. Flue gas typically contains 0.5–5 ppm NO2 and 10–100 ppm NO. NO2 at 1 ppm in the flue gas appears to cause significant amine oxidation in pilot plant testing. PZ solution can easily absorb NO2, and it is hypothesized that NO2 can catalytically oxidize PZ through free-radical propagation. The issue may not be solved by a NO2 pre-scrubber since the coexistence of NO and O2 in the flue gas will keep producing non-negligible amounts of NO2 in the ductwork and the absorber after the NO2 incoming with the flue gas has been scrubbed. In addition, NO2 may not only oxidize PZ but also the intermediate degradation products, and it is unknown if the existence of dissolved iron influences the oxidation by NO2. Previous workers have also shown that NO2 is the stoichiometric source of nitrosamine. A comprehensive analysis of NO2 oxidation is needed to address solvent management and its health/environmental impact. The new high gas flow (HGF) reactor focuses only on the absorber environment and is simpler to interpret because it does not include oxidation at high temperatures and by dissolved metal catalysts from corrosion. This paper presents the results of HGF experiments and shows evidence to support a hypothesis of amine oxidation catalyzed by NO2, presents the synergic effect of NO2 and iron on amine oxidation, points out the different effects of NO2 in clean and degraded solvents, and demonstrates that NO2 not only can oxidize amines but also their degradation products.

NO2, iron, piperazine (PZ), solvent oxidation, sol↗
DOE OSTI2022

Anomalies in the topology of the temperature fluctuations in the cosmic microwave background: An analysis of the NPIPE and FFP10 data releases

We present a topological analysis of the temperature fluctuation maps from the Planck 2020 Data Release 4 NPIPE dataset and the Planck 2018 Data Release 3 FFP10 dataset. We performed a multiscale analysis in terms of the homology characteristics of the maps, invoking relative homology to account for the analysis in the presence of masks. We performed our analysis for a range of smoothing scales spanning sub- and super-horizon scales corresponding to a full width at half maximum (FWHM) of 5',10',20',40',80',160',320', and 640', and employed simulations based on the standard model for comparison, which assumes the initial fluctuation field to be an isotropic and homogeneous Gaussian random field. Examining the behavior of topological components, represented by the 0D homology group, we find the observations to be approximately 2σ or less deviant from the simulations for all resolutions and scales for the NPIPE dataset. For the FFP10 dataset, we detect a 2.96σ deviation between the observations and simulations at N = 128, FWHM = 80'. For the topological loops, represented by the first homology group, the simulations and observations are consistent within 2σ for most resolutions and scales for both the datasets. However, for the NPIPE dataset, we observe a high deviation between the observation and simulations in the number of loops at FWHM = 320', but at a low dimensionless threshold ν = –2.5. Under a Gaussian assumption, this would amount to a deviation of ~4σ. However, the distribution in this bin is manifestly non-Gaussian and does not obey Poisson statistics either. In the absence of a true theoretical understanding, we simply note that the significance is higher than what may be resolved by 600 simulations, yielding an empirical p-value of at most 0.0016. Specifically in this case, our tests indicate that the numbers arise from a statistically stable regime, despite being based on small numbers. For the FFP10 dataset, the differences are not as strong as for the NPIPE dataset, indicating a 2.77σ deviation at this resolution and threshold. The Euler characteristic, which is the alternating sum of the ranks of relative homology groups, reflects the deviations in the components and loops. To assess the significance of combined levels for a given scale, we employed the empirical and theoretical versions of the χ 2 test as well as the nonparametric Tukey depth test. Although all statistics exhibit a stable distribution, we favor the empirical version of the χ 2 test in the final interpretation, as it indicates the most conservative differences. For the NPIPE dataset, we find that the components and loops differ at more than 95%, but agree within the 99% confidence level with respect to the base model at N = 32, FWHM = 320'. The Euler characteristic at this resolution displays a per mil deviation. In contrast, the FFP10 dataset shows that the observations are consistent with the base model within the 95% confidence level, at this and smaller scales. This is consistent with the observations of the Planck analysis pipeline via Minkowski functionals. For the largest smoothing scale, N = 16, FWHM = 640', both datasets exhibit an anomalous behavior of the loops, where FFP10 data exhibit a deviation that is larger by an order of magnitude than that of the NPIPE dataset. In contrast, the values for the topological components and the Euler characteristic agree between observations and model to within a confidence level of 99%. However, for the largest scales, the statistics are based on low numbers and may have to be regarded with caution. Even though both datasets exhibit mild to significant discrepancies, they also exhibit contrasting behaviors at various instances. Therefore, we do not find it feasible to convincingly accept or reject the null hypothesis. Disregarding the large-scale anomalies that persist at similar scales in WMAP and Planck, observations of the cosmic microwave background are largely consistent with the standard cosmological model within 2σ.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Data-Driven Understanding of Low-to-Moderate Income Customers’ Adoption and Financial Qualification in Community Solar (Final Technical Report)

When Solstice began working in the community solar industry, it quickly became clear that there was a wide disparity along race and class lines in terms of what kind of household traditional solar offerings benefited. Solstice is an organization that aligns itself to the principles of a Just Transition, or the concept that a transition to a green economy should benefit and prioritize historically marginalized groups of people. Given that low-income communities are disproportionately burdened by our current polluting fossil fuel economy, Solstice set out to investigate the root causes of the exclusion of low to moderate income (LMI) households in the community solar market. As we worked more and more with financiers, developers, and LMI households, we recognized that significant barriers to entry in a developer-owned project were credit threshold requirements. A FICO score of 750 and higher discriminates against LMI households that are not financially stable enough to take on multiple lines of credit (or who may not have been deemed credit worthy enough to access a line of credit) yet who may have been reliable utility customers. As Solstice began looking further into preliminary data and speaking to community-based organizations (CBOs) that serve LMI households, we found our hypothesis to be worth investigating; there was indeed a subset of LMI households with poor FICO scores (or no FICO score at all) that had perfect bill payment history. Though initially Solstice was intent on gathering a body of data to prove or disprove this hypothesis, we were also concerned that all this proof of a financially stable and reliable customer was not being incorporated into FICO, and wondered if such a score would be possible. After preliminary research into the existence of alternative scores, Solstice realized that many mission-driven lending institutions rely on alternative metrics that are formulated for their specific industry. However, we also realized that community solar did not have an alternative credit underwriting mechanism, though there was great need from solar financiers for one. We anticipated that the creation of an EnergyScore would contribute to financiers’ need to qualify more people, as these entities are desperately looking for ways to lower the cost of customer acquisition. FICO turns away nearly 50% of potential customers (according to our own acquisition experience), and much of the community solar industry is realizing that FICO is not the perfect qualifying mechanism. Additionally, with a grounding in energy justice, just transitions, and climate justice, Solstice recognizes the need for a solution that addresses a more urgent need for LMI households to access renewable energy savings and relieve energy burdens. With funding from the Department of Energy, we gathered the data necessary to build the EnergyScore, reached out to mission-driven developers willing to test the metric, and secured several demonstration projects to pilot the EnergyScore. After acquiring customers for these demo projects using the EnergyScore, we will be continuously collecting customer payment behavior data. Though it goes beyond the scope of this project, we plan to disseminate this de-identified data with the wider community solar industry, which includes not only financiers and developers, but other mission-driven nonprofits, solar cooperatives, community-based organizations, environmental justice activists, and academics. While we intend to disprove the notion that LMI households cannot be included in projects without acutely increasing the risk to project finances, we also hope the data can be used to negotiate better pricing of systems and terms of ownership for community groups seeking to build inclusive projects.

14 SOLAR ENERGY↗
DOE OSTI2026

Plant Bioengineering Atlas: A Knowledge Graph of Genes, DNA Constructs, and Plant Traits.

Plant bioengineering has generated tens of thousands of genotype-to-phenotype relationships, but this knowledge remains fragmented across narrative literature and difficult to use computationally. Inconsistent descriptions of DNA constructs, host species, and traits, including variable species names, omitted regulatory elements, and inconsistent gene symbols, impede data reuse, comparative analysis, and design-build-test-learn cycles. Here, we present the Plant Bioengineering Atlas, a literature-mined, ontology-grounded knowledge base assembled using an artificial intelligence (AI)-aided extraction pipeline. A large language model parsed open-access primary research articles to generate structured, provenance-anchored records of engineered genes, modification types, promoter-gene-terminator constructs, host species, target traits, and reported phenotypes, with every record traceable to its source. The current release contains 14,358 curated records encompassing 6,998 distinct genes across 436 plant species from 6,452 papers published between 2000 and 2026. Corpus analysis reveals that experiments are concentrated in a small group of model and crop species, disease and pathogen resistance is the most frequently engineered trait class, and constitutive regulatory parts (particularly the CaMV 35S promoter and NOS terminator) remain pervasive. Two in five records omit one or both flanking regulatory elements (i.e., promoter and terminator), while only 23.4% describe cassettes in which both elements resolve to named part classes, exposing a systematic reproducibility gap. We organize these data into a knowledge graph linking genes, constructs, species, and traits; provide access through an interactive web portal; and propose an AI-compatible documentation standard for AI-ready reporting. The Plant Bioengineering Atlas provides a foundation for data-driven hypothesis generation and AI-aided plant biodesign.

, Genes, DNA Constructs↗
DOE OSTI2026

PAC in DESI. II. Galaxy-halo connection into the $10^{6}{\rm M}_{\odot}$ frontier

Understanding dwarf galaxy formation is crucial for testing dark matter models and reionization physics. However, constructing stellar-mass complete spectroscopic samples at low masses is increasingly difficult, and the potential existence of a local void complicates studies in an average environment. The Photometric object Around Cosmic webs (PAC) method, which combines deep photometric and spectroscopic data to measure the excess surface density $\bar{n}_2w_{\rm{p}}(r_{\rm{p}})$ of photometric objects around spectroscopic tracers, offers a promising path forward. We model 349 $\bar{n}_2w_{\rm{p}}(r_{\rm{p}})$ measurements from DESI Y1 BGS and DECaLS, reaching $M_*=10^{6.4}\,{\rm M}_{\odot}$, using a stellar mass-halo mass relation (SHMR)-based subhalo abundance matching framework applied to two high-resolution $N$-body simulations from the Jiutian suite. The resulting SHMR is constrained down to $M_{\rm h}\simeq10^{8.0}\,h^{-1}{\rm M}_{\odot}$, revealing a clear upturn at $\sim10^{10.0}\,h^{-1}{\rm M}_{\odot}$ toward lower masses, indicating rising star-formation efficiency (SFE) in small haloes. This feature persists under extensions of the model that allow mass-dependent scatter, reionization-induced suppression of the halo occupation fraction, galaxy assembly bias, and alternative cosmologies. Combining with the results from Paper I, we find that central red galaxies dominate the low-mass regime. Our results motivate a hypothesis in which SFE is significantly higher than previously thought prior to reionization, enabling relatively massive galaxies to form in small haloes. These systems are subsequently quenched by the UV background, producing the central red dwarf galaxies observed. Finally, we obtain $3σ$ and $5σ$ upper mass bounds of $10^{8.80}\,h^{-1}{\rm M}_{\odot}$ and $10^{10.24}\,h^{-1}{\rm M}_{\odot}$ on the smallest haloes required to exist.

Xu, Kun [Pennsylvania U.; Durham U., ICC; Tsung-Da↗
DOE OSTI2023

Is land use producing robust signals in future projections from Earth system models, all else being equal?

Abstract We use six Earth system models (ESMs) run under SSP3-7.0, a scenario characterized by a relatively large land use change (LUC) over the 21st century, and under a variant of the same scenario where a significantly different pattern of LUC, taken from SSP1-2.6, was used, all else being equal. Our goal is to identify changes in climate extremes between the two scenarios that are statistically significant and robust across the ESMs. The motivation for this study is to test a long-held assumption of the shared socio-economic pathway-representative concentration pathway (SSP-RCP) scenario framework: that the signal from LUC can be safely disregarded when pairing different SSPs to the compatible RCPs, where compatibility only considers global radiative forcing, predominantly determined by well-mixed greenhouse gasses emissions. We analyze extremes of daily minimum and maximum temperatures and precipitation, after fitting non-stationary generalized extreme value distributions in a way that borrows strength along the length of the simulation (2015–2100) and across initial condition ensembles. We consider changes in the 20 year return levels (RL20s) of these metrics by 2100, and focus on eight locations where LUC is large within each scenario, and strongly differs between scenarios, averaging the RL20s over a neighborhood characterized by the same LUC to enhance the signal to noise. We find that precipitation extremes do not show significant differences attributable to LUC differences. For temperature extremes (cold and hot) results are mixed, with some location-index combination showing significant results for some of the ESMs but not all, and not many coherent changes appearing for indices across regions, or regions across indices. These ESMs are representative of what is typically adopted as the source of climate information for impact studies, when the SSP-RCP framework is put to use. Overall, our analysis suggests that the hypothesis to pair SSPs to RCPs in a flexible fashion is overall defensible. However, the appearance of some coherence in a few locations and for some indices invites further investigation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Measurements and computational analysis of the natural decay of 176 Lu

Background: Mainly because of its long half-life and despite its scientific relevance, spectroscopic measurements of 176 Lu forbidden β decays are very limited and lack formulation of shape factors. A direct precise measurement of its Q value is also presently unreported. In addition, the description of forbidden decays provides interesting challenges for nuclear theory. The comparison of precise experimental results with theoretical calculations for these decays can help to test underlying models and can aid the interpretation of data from other experiments. Purpose: Perform the first precision measurements of 176 Lu β-decay spectra and attempt the observation of its electron capture decays, as well as perform the first precision direct measurement of the 176 Lu β-decay Q value. Compare the shape of the precisely determined experimental β spectra to theoretical calculations, and compare the end point energy to that obtained from an independent Q value measurement. Method: Here, the 176 Lu β-decay spectra measurements and the search for electron capture decays were performed with an experimental setup that employed lutetium-containing scintillator crystals and a NaI(Tl) spectrometer for coincidence counting. The β decay Q value was determined via high-precision Penning trap mass spectrometry (PTMS) with the LEBIT facility at the National Superconducting Cyclotron Laboratory. The β-spectrum calculations were performed within the Fermi theory formalism with nuclear structure effects calculated using a shell model approach. Results: Both β transitions of 176 Lu were experimentally observed and corresponding shape factors formulated in their entire energy ranges. The search for electron capture decay branches led to an experimental upper limit of 6.3×10 –6 relative to its β decays. The 176 Lu β-decay and electron capture Q values were measured using PTMS to be 1193.0(6) and 108.9(8) keV, respectively. This enabled precise β end point energies of 596.2(6) and 195.3(6) keV to be determined for the primary and secondary β decays, respectively. The conserved vector current hypothesis was applied to calculate the relativistic vector matrix elements. The β-spectrum shape was shown to significantly depend on the Coulomb displacement energy and on the value of the axial vector coupling constant gA, which was extracted according to different assumptions. Conclusion: The implemented self-scintillation method has provided unmatched observations of 176 Lu, independently validated by the first direct measurements of its β-decay Q value by Penning trap mass spectrometry. Theoretical study of the main β transition led to the extraction of very different effective gA and log10f values, showing that a high-precision description of this transition would require a realistic nuclear structure with nucleus deformation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

CPAP Ventilators Needed for Rapid Response to COVID-19 by Modification of CPAP Equipment

Early on in the COVID-19 pandemic, potential ventilator shortages were a critical issue identified by national health care providers. Capacity modeling at the time suggested patient demand may exceed ventilator supply. Thus, the challenge became finding an urgent interim solution to meet health care needs. Our initial hypothesis was that CPAP technology could be modified to provide similar functionality to a ventilator, relieving demand and allowing physicians to decide which patients need high end machines, ultimately saving lives. In conjunction with medical experts and pulmonologists, we were able to identify three key thrusts associated with this research problem: (1) modification of CPAP technology to allow for 02 input that would be capable of providing ventilation; (2) development of an alarming function that would provide real-time audible alarms to alert medical personnel to critical conditions, which would be used inline with CPAP technology; and (3) a method of sterilizing expiratory air from such a system in order to protect medical personnel from biohazard, since CPAPs vent to the atmosphere. We were unable to realize results for thrust 1 (CPAP modification for 02); we identified potential safety issues associated with utilizing medical grade oxygen with a common CPAP device. In order to characterize and mitigate these issues, we would need to partner closely with a device manufacturer; such a partnership could not be achieved in the timeframe needed for this rapid response work. However, we determined that some medical grade BiPAP devices do not need this modification and that the significant progress on thrusts 2 and 3 would be sufficient to buy down risk of a massive ventilator shortage. Our team built a prototype alarm system that can be utilized with any assistive respiratory device to alert on all key conditions identified by medical personnel (high pressure, low pressure, apnea, loss of power, low battery). Finally, our team made significant progress in the rapid prototyping and demonstration of an inline UV air purifier device. The device is cost efficient and can be manufactured at scale with both commercially available and additively manufactured parts. Initial tests with SARS-CoV-2 analog bacteriophage MS2 show 99% efficacy at reducing bioburden. Following a successful demonstration of the prototype device with medical personnel, we were able to obtain follow-on (non-LDRD) funding to provide additional device characterization, validation, and production in order to respond to an immediate regional need.

42 ENGINEERING↗
DOE OSTI2026

matsim-agents v1.0

matsim-agents is a multi-agent AI framework for atomistic materials simulation and discovery. It orchestrates large language models (LLMs), machine-learned interatomic potentials (MLIPs), and DFT codes into a single agentic loop running on laptops and DOE leadership-class supercomputers. MULTI-AGENT ORCHESTRATION A LangGraph state machine with three nodes: a Planner that converts a natural-language research objective into structured tasks; an Executor that dispatches atomistic tools and loops until the queue is empty; and an Analyst that summarizes results into a human-readable report. State is checkpointed after every step and human-in-the-loop gates can be inserted at any edge. HYPOTHESIS-DRIVEN DISCOVERY CHAT An interactive REPL (matsim-agents chat) that couples LLM dialogue with atomistic simulation. Chemical formulas are automatically detected in conversation turns and trigger a full crystal-phase exploration: structure generation → relaxation → stability scoring → result injection back into the conversation, creating a closed hypothesis-refinement loop. CRYSTAL PHASE ENUMERATION Given a composition, the phase explorer enumerates prototypes by stoichiometry: elemental (fcc/bcc/hcp/sc/diamond), binary 1:1 (rocksalt/CsCl/zincblende/ wurtzite/fluorite/rutile), ternary 1:1:3 (cubic perovskite), ternary 1:2:4 (perovskite + spinel), quaternary 1:1:2:6 (Fm-3m double perovskite). 2-D prototypes (graphene, h-BN, MoS2 2H/1T) and multilayer stacking are also supported via --include-2d and --num-layers. SUPERCELL GENERATION AND SITE DECORATION Auto-tiling to a minimum atom count (--min-atoms), explicit NxNxN tiling (--supercell), symmetry-distinct site decorations (--n-orderings), and isotropic lattice-scale sweeps (--lattice-scales) for volume bracketing. MLFF RELAXATION AND STABILITY SCORING HydraGNN (multi-headed GNN) drives structure relaxation via ASE with FIRE, BFGS, or BFGSLineSearch. Stability output: delta-E/atom ranking across phases and a max-residual-force dynamical-stability proxy. Other MLIPs (MACE, NequIP, Orb) can be plugged in through the same interface. DFT BACKENDS Quantum ESPRESSO pw.x and VASP 6.6 are first-class labellers. Both have validated GPU builds and SLURM/PBS launchers for three DOE platforms: Frontier (AMD MI250X, ROCm), Aurora (Intel PVC, oneAPI), Perlmutter (NVIDIA A100, CUDA). QE produces ~100 binaries (pw.x, ph.x, epw.x, ...). VASP supports scf, relax, vc-relax, and vc-relax-shape run types. ACTIVE-LEARNING LOOP matsim-agents al run CONFIG.yaml drives an iterative HydraGNN-DFT loop: MD generates candidates → ensemble/MC-dropout uncertainty selects the most informative → DFT labels them in parallel inside one allocation → dataset grows → HydraGNN retrains → repeat. DFT backend is a single YAML toggle (dft.backend: vasp | qe). LLM-generated seed structures are supported (no curated POSCAR library needed). Config uses ${VAR}, ${VAR:-default}, ${VAR:?msg} shell-style substitution for cross-user/cross-site portability. LLM BACKENDS Ollama (local, default), vLLM (HPC multi-GPU serving), OpenAI, Anthropic, HuggingFace Transformers+Accelerate. Selected at runtime via flag or env var with no code changes. HPC PORTABILITY Same Python entry points run on Frontier (ROCm 7.2), Aurora (oneAPI), and Perlmutter (CUDA 12). DFT and ML stacks are never co-loaded in the same shell; they couple through the scheduler and filesystem. Advanced multi-node launchers (serve, discovery-chat, single-relaxation, active-learning, QE warm-start) are provided for all three platforms. CODABENCH COMPETITION BUNDLE A self-contained benchmark: 159 atomistic test structures across 11 material classes, 5 tasks (formation energy, forces, ML relaxation, AI-DFT relaxation, phase stability ranking), public/private leaderboard split (30/70), and four ready-to-run baselines: MACE-MP-0, HydraGNN, UMA, AllScAIP.

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗